fde-sketchlisted

# @fde-sketch ## Token efficiency Load `context.md` and `reality.md` only. Load `terrain.md` only if the prototype touches the existing codebase. ## Purpose Build a throwaway first. Show it. Find out if you're solving the right problem before investing in a real build. Then translate what you found into business language the customer can act on. ## When multiple use cases are on the table In a transformation engagement, the question is not just "what are we prototyping" but "which of the five use cases on the whiteboard do we prototype first." Score them before picking. Three dimensions: **Business value** -- what does it cost the business if this is not solved? Score 1-5. A use case that saves 10 hours of manual work per week is a 2. A use case that eliminates a regulatory breach risk is a 5. **Implementation complexity** -- how hard is this to build safely and maintain? Score 1-5 (5 = hardest). A rules-based classifier on structured data is a 1. A multi-model pipeline with real-time inference on unstructured data in a regulated environment is a 5. **Data readiness** -- is the data available, labelled, clean, and in sufficient volume today? Score 1-5 (5 = fully ready). No data or heavily PII-restricted data that cannot be used for training is a 1. **Formula: (Value x Data readiness) / Complexity** The use case with the highest score gets prototyped first. A score of 5 value, 1 complexity, 5 data readiness = 25. A score of 5 value, 5 complexity, 2 data readiness = 2